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  • 标题:Network Topology Evolution based on Traffic Distribution and Increase
  • 本地全文:下载
  • 作者:Xiangqian Chen ; Kia Makki ; Kang Yen
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2008
  • 卷号:8
  • 期号:10
  • 页码:42-46
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:

    Following the traffic of a backbone increase near to the capacity of the network, the evolution of backbone topology takes place. In this paper, three main types of evolution methods: link upgrading only method, node upgrading method, and the combination of previous two are explored. To shunt the saturated traffic efficiently, we propose several node upgrading algorithms, Traffic Adaptive Topology gEnerators (TATEs), based on the condition of current traffic distribution and node burden. TATEs choose the congested link as the main shunting object. The difference among TATEs lies that they have diverse strategies to choose a node in the congested link as the second shunting aim. Simulation shows that: the type of TATEs that picks the burdened node in the saturated link as the second shunting object has the most effective shunting result. Compare with most of current topology generators such as [BRITE] in [1] which consider little about traffic increase distribution, TATEs are more efficient to satisfy traffic increase.

  • 关键词:

    Topology evolution, link upgrading, node upgrading, saturated link, traffic increase model, burdened node, traffic shunting

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